Aesthetics, Cosmopolitics and Design

             

 

 

 

 

 

 

 

A Creative Ontological analysis of collective imagery during Co-Design for Service Innovation

Priscilla Chueng-Nainby, John Lee, BingXin Zi, Astury Gardin

University of Edinburgh (4)

p.chuengnainby@ed.ac.uk

Keywords: Co-Design, Design Ontology, Service innovation, Machine Learning

Abstract

This paper describes an ontological attempt in the understanding of co-design activity in the wild within the context of service innovation. The research has an aim to analyse the transformation of ideas during co-design by examining informal data from a workshop that inspired villagers in Turkey to innovate collaboratively. Contrary to the often process-oriented analysis of co-design activity, the workshop facilitates designing by envisioning and enacting participants’ collective imagery in physical forms in an iterative cycle of deconstruction, construction and reconstruction. We report an understanding of the ontology established to describe and analyse the informal data collected from the physical forms of collective imagery. A machine learning approach is used to underpin assumptions made in the understanding of the activity based on the ontology. The analysis suggests the frequency and relevancy of ideas significantly influenced the possibility that an idea will become part of a design solution. An evaluation of the machine learning analysis delivers insights into the understanding of data collected during co-design in the wild.

This paper is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International licence.

download the paper (PDF)

Cite this paper: Chueng-Nainby, P., Lee, J., Zi, B., Gardin, A. (2016). A Creative Ontological Analysis of Collective Imagery during Co-Design for Service Innovation. Proceedings of DRS 2016, Design Research Society 50th Anniversary Conference. Brighton, UK, 27–30 June 2016.

This paper will be presented at DRS2016, find it in the conference programme


Take part in the discussion: Your comments